Adctoolbox Contributor Guide

ADCToolbox Maintainer Guide

This skill is for repository maintenance only.

Use adctoolbox-user-guide when the task is:

• choosing a tool from the library
• writing user-facing Python example code
• analyzing ADC data with the package

Use this skill when the task is:

• adding or changing a public API
• modifying package exports
• adding tests or fixing broken tests
• changing packaging, CLI commands, or bundled skill assets
• updating repository examples or maintainer docs

For test execution details, open references/testing-guide.md.

1. Public API Maintenance

The top-level Python API is controlled by python/src/adctoolbox/__init__.py.

If you add a new public flat import:

1. add it in the relevant submodule
2. export it in the submodule __init__.py
3. register it in top-level adctoolbox/__init__.py with _export(...)
4. update examples and user-facing skill docs if the new API is user-visible

Do not expose helpers with leading _.

Some public tools are intentionally not flat-exported, such as:

• adctoolbox.siggen.ADC_Signal_Generator
• adctoolbox.toolset.generate_aout_dashboard
• adctoolbox.toolset.generate_dout_dashboard
• adctoolbox.calibration.calibrate_weight_sine_lite
• adctoolbox.fundamentals.validate_aout_data
• adctoolbox.fundamentals.validate_dout_data

If you change these interfaces, update the user guide skill because agents rely on that routing.

2. Return-Shape Policy

For new Python public APIs, prefer dict returns with stable snake_case keys.

Do not introduce new tuple-style public returns unless there is a very strong compatibility reason.

Current legacy exceptions still in the package include:

• find_coherent_frequency
• analyze_bit_activity
• analyze_overflow
• analyze_enob_sweep
• fit_static_nonlin
• calibrate_weight_sine_lite
• convert_cap_to_weight

Important correction:

• analyze_weight_radix currently returns a dict, not a bare array

If you change a return shape, update:

1. code
2. tests
3. examples
4. bundled skill docs under python/src/adctoolbox/_bundled_skills/skills/

3. Bundled Skills

Skills are maintained only under:

• python/src/adctoolbox/_bundled_skills/skills/

When editing a skill:

1. keep SKILL.md short and use references only when needed
2. prefer routing to packaged examples over duplicating long tutorials
3. verify the installer CLI still installs the expected files

4. What Must Stay In Sync

When a public API changes, do not stop at code changes.

• update affected examples under python/src/adctoolbox/examples/
• update bundled skill docs if the routing or return shape changed
• update tests that pin exports or return keys
• correct README snippets only when they would mislead users

Treat source exports and runnable examples as the canonical user-facing API.

5. Packaging And CLI Changes

If you add or modify a CLI:

• register it in python/pyproject.toml
• keep behavior non-destructive by default
• support explicit overwrite/upgrade flags for replacement flows
• validate with a temp destination, not the real ~/.codex/skills

For Codex skill installation specifically:

• installers must require an explicit --dest; do not write to $CODEX_HOME/skills or ~/.codex/skills implicitly
• status checks should use adctoolbox-install-skill --status --dest <skills-dir>
• normal installs should only install adctoolbox-user-guide
• dev-only skill installation should require explicit --dev or --all
• editable skill installation should require explicit --editable and use symlinks only for local development